The proper development, modeling and improvement of biopharmaceutical cleaning procedures are often time-consuming and impractical when production equipment is otherwise in use. Laboratory studies on coupons of representative biopharmaceutical manufacturing materials of construction (MOC) have long been the model on which cleaning regimens have been tested. Coupons, in and of themselves, are adequate models of the surfaces that need to be cleaned. However, the cleaning procedures typically used on the coupons do not sufficiently exemplify the conditions and phases of a Cleaning-in-Place (CIP) cycle within a production vessel.
The generalized phases of CIP procedures are rinse, chemical wash, rinse. But in designing a cleaning cycle for new or not well-understood soiling solutions in biopharmaceutical manufacturing processes, the difficult questions concern the fundamental components of cleaning details. Regulatory agencies continually inquire about cleaning programs, requiring an immense expenditure of resources and capital by commercial biopharmaceutical companies simply to document cleaning procedures. An efficient method of expediting cleaning development, providing experimental justification of existing cleaning methodologies, and resolving new cleaning issues has been the use of laboratory or bench scale cleaning studies on small MOC coupons. These bench scale studies can be performed with relative ease and low cost, especially because they obviate halting the manufacturing process to allow use of the full-scale manufacturing equipment for development runs. Any stop in marketable production affects the bottom-line profitability that, in turn, allows other company operations to continue. When properly designed, bench scale studies may provide an excellent model for various elements of full scale cleaning qualifications. Some of the needs of bench scale studies include access to process soils or representative model soils and conservative but pertinent experimental design and cleaning process modeling.
Appropriate soil selection, accurate process modeling and robust experimental design are the three pillars of comprehensive cleaning cycle development. Of these, process modeling has been the least investigated as to its efficiency and effectiveness. Biopharmaceutical drug substances are often in short and expensive supply. For this reason the engineers and scientists in charge of formulating a cleaning regime have turned to small MOC coupons in an attempt to model the use of manufacturing cleaning chemicals and cleaning cycles. A cleaning process model should include an appropriate combination of contact time, temperature, chemistry and representative cleaning action. The first three components are often studied in a static soak or a mildly agitated environment. This is often referred to as a most conservative approach which, when scaled up, would allow for a margin of safety or robustness in the cleaning process. The problem with this approach is that the soaking method may inaccurately represent the ratio of cleaning solution to soil per surface area. Furthermore, static soaking does not accurately reproduce the representative sheeting or cascading action that interior surface vessels receive when CIP cleaning chemicals are introduced via devices such as spray balls and spray wands.
The pressure and flow rate at which rinsing and cleaning solutions contact a vessel surface can vary tremendously. There are instances where a piece of equipment is cleaned manually via an ambient temperature, static soak in a dilute cleaning solution. There are also instances where a piece of equipment to be cleaned is blasted with heated, high concentration chemicals at pressures of greater than twenty pounds per square inch and a flow rate greater than forty five liters per minute. These examples may be extremes, but cycle parameters should be tailored to the equipment, process and soil cleanability. When encountering a process solution for the first time, it may be difficult to determine suitable cleaning contact times, temperatures, chemical concentrations and external energies or action necessary to effectively and efficiently remove unwanted soil from manufacturing process equipment. These variables should be carefully considered and used in combination in order to achieve the level of cleaning necessary without taxing any variable to an extreme that may not be sustainable by the cleaning equipment, the equipment being cleaned or the resources of the manufacturer themselves. Intimate understanding of the cleaning dynamics specific to a piece of equipment is integral in the development of a robust and implementable cleaning cycle. However, since this can be a long and arduous process, a suitable model system is paramount in maximizing the feasibility of proper development by minimizing manufacturing equipment downtime.
The choice of a proper manufacturing solution, or soiling solution from the cleaning validation perspective, on which to conduct cleaning development studies may either be a rather simple issue of immediate need to validate the cleaning of a specific soil, or it may be a more complex issue that requires more discussion and scientific logic to determine. Choosing the appropriate and most challenging process soil to conduct cleaning validation in the biopharmaceutical industry has traditionally been a best guess decision process. In biotechnology processes where numerous culture media and purification buffers are the norm for manufacturing a single product, the choice of a cleaning validation “worst case” challenge soil is typically imprecise, or one of historical precedent without much scientific analysis. Validation engineers are often pressed for scientific justification concerning their choice of representative challenge soils, especially in multi-product facilities where the significance is multiplied by the number of different products. New biopharmaceutical manufacturing processes may be even more difficult to assess since there may be little empirical information regarding which solutions historically present the greatest cleaning challenge.
Validation engineers responsible for cleaning validation invariably find themselves faced with the daunting question, “What is your worst case soil?” The answer to this question is simple when one is dealing with a pre-existing piece of equipment that is dedicated to a single product at a single process step. In this instance, the answer is simply the soil currently being used in or contacting that piece of equipment. However, in the case of an established multi-product/multi-soil piece of equipment or new biopharmaceutical manufacturing processes, the choice of a worst case challenge soil poses more of a quandary.
The choices of a worst case soil for cleaning validation may be numerous, with a vast diversity of soiling solution components. While it may be preferable to validate the cleaning of every soil to enter that equipment, resources and time greatly limit the number of validation runs that can be realistically conducted. Furthermore, for new manufacturing processes situations, not all process solutions may be enumerated at the time the cleaning validation is performed. Additionally, to operate more efficiently, an increasing number of corporations are positioning themselves as multi-product facilities in order to minimize risk and optimize capacity utilization. This push toward economic efficiency drives the need for more robust and encompassing validation studies that will allow for timely product changeover events. Cleaning validation presents one area where, when carefully thought out, efficiencies may be gained.
The choice of a cleaning validation worst case challenge solution that covers numerous solutions from various products would mean only one soiling solution per protocol execution. Depending on the chemical composition and nature of the soil chosen, that validation may even cover the cleaning validation of future, as of yet, unknown process solutions and soils. As a result, it is desirable to have an improved method to determine and compare the theoretical cleaning feasibility, or “cleanability”, of various process or equipment soiling streams for both single and multi-product biopharmaceutical facilities.